Global distance test

The global distance test (GDT), also written as GDT TS to represent "total score", is a measure of similarity between two protein structures with identical amino acid sequences but different tertiary structures. It is most commonly used to compare the results of protein structure prediction to the experimentally determined structure as measured by X-ray crystallography or protein NMR. The metric is intended as a more accurate measurement than the more common RMSD metric, which is sensitive to outlier regions created by poor modeling of individual loop regions in a structure that is otherwise reasonably accurate. GDT_TS measurements are used as major assessment criteria in the production of results from the Critical Assessment of Structure Prediction (CASP), a large-scale experiment in the structure prediction community dedicated to assessing current modeling techniques and identifying their primary deficiencies.[1][2][3] In general, the higher GDT_TS is, the better a given model is in comparison to reference structure.

The GDT score is calculated as the largest set of amino acid residues' alpha carbon atoms in the model structure falling within a defined distance cutoff of their position in the experimental structure. It is typical to calculate the GDT score under several cutoff distances, and scores generally increase with increasing cutoff. A plateau in this increase may indicate an extreme divergence between the experimental and predicted structures, such that no additional atoms are included in any cutoff of a reasonable distance.

The high accuracy version of the GDT measure is called GDT-HA. It uses smaller cut off distances (half the size of GDT_TS) and thus is more rigorous.[4]

See also

References

  1. Zemla A, Venclovas C, Moult J, Fidelis K (1999). "Processing and analysis of CASP3 protein structure predictions". Proteins. S3: 22–29. doi:10.1002/(sici)1097-0134(1999)37:3+<22::aid-prot5>3.3.co;2-n. PMID 10526349.
  2. Zemla A, Venclovas C, Moult J, Fidelis K (2001). "Processing and evaluation of predictions in CASP4". Proteins. 45 (S5): 13–21. doi:10.1002/prot.10052. PMID 11835478.
  3. Zemla A (2003). "LGA: A method for finding 3D similarities in protein structures". Nucleic Acids Research. 31 (13): 3370–3374. doi:10.1093/nar/gkg571. PMC 168977Freely accessible. PMID 12824330.
  4. Read, Randy J.; Chavali, Gayatri (2007). "Assessment of CASP7 predictions in the high accuracy template-based modeling category". Proteins. 69 (S8): 27–37. doi:10.1002/prot.21662. PMID 17894351.

External links

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